Expert Recommendations Based on Opinion Mining of User-Generated Product Reviews
Article first published online: 25 OCT 2013
© 2013 Wiley Periodicals, Inc.
Volume 31, Issue 1, pages 165–183, February 2015
How to Cite
2015), Expert Recommendations Based on Opinion Mining of User-Generated Product Reviews, Computational Intelligence, 31, 165–183, doi: 10.1111/coin.12021, and (
- Issue published online: 10 FEB 2015
- Article first published online: 25 OCT 2013
- Manuscript Accepted: 25 SEP 2013
- Manuscript Revised: 8 AUG 2013
- Manuscript Received: 18 JUL 2012
- recommender systems, opinion mining, natural language processing, product reviews
In this article, we introduce the idea of expert recommendations whose objective is to relate review comments with users’ tasks or expectations. We propose to use fine-grained information such as opinions and suggestions extracted using natural language processing techniques from user reviews about products, to improve a recommendation system. While typical recommender systems compare a user profile with some reference characteristics to rate unseen items, they rarely make use of the content of reviews that users have provided on a given product. In this article, we present the application of an opinion extraction system to extract opinions and suggestions from the content of the reviews, the use of the results to compare other products with the reviewed one, and eventually the recommendation of better products to the user. The recommendations are given a confidence weight by using a trust social network.